Physics-informed machine learning with conditional Karhunen-Loève expansions
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Tartakovsky, A. M. (ORCID:000000032375318X)↗
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Dark aspects of massive spinor electrodynamics
We investigate the cosmology of massive spinor electrodynamics when torsion is non-vanishing. A non-minimal interaction is introduced between the torsion and the vector field and the coupling constant between them plays an important role in subsequential cosmology. It is shown that the mass of the vector field and torsion conspire to generate dark energy and pressureless dark matter, and for generic values of the coupling constant, the theory effectively provides an interacting model between them with an additional energy density of the form ∼ 1/a{sup 6}. The evolution equations mimic ΛCDM behavior up to 1/a{sup 3} term and the additional term represents a deviation from ΛCDM. We show that the deviation is compatible with the observational data, if it is very small. We find that the non-minimal interaction is responsible for generating an effective cosmological constant which is directly proportional to the mass squared of the vector field and the mass of the photon within its current observational limit could be the source of the dark energy.
79 ASTRONOMY AND ASTROPHYSICS↗
Greenland Surface Mass Balance as Simulated by the Community Earth System Model. Part I: Model Evaluation and 1850–2005 Results
The modeling of the surface mass balance (SMB) of the Greenland Ice Sheet (GIS) requires high-resolution models in order to capture the observed large gradients in the steep marginal areas. Until now, global climate models have not been considered suitable to model ice sheet SMB owing to model biases and insufficient resolution. This study analyzes the GIS SMB simulated for the period 1850–2005 by the Community Earth System Model (CESM), which includes a new ice sheet component with multiple elevation classes for SMB calculations. The model is evaluated against observational data and output from the regional model Regional Atmospheric Climate Model version 2 (RACMO2). Because of a lack of major climate biases, a sophisticated calculation of snow processes (including surface albedo evolution) and an adequate downscaling technique, CESM is able to realistically simulate GIS surface climate and SMB. CESM SMB agrees reasonably well with in situ data from 475 locations ($r$ = 0.80) and output from RACMO2 ($r$ = 0.79). The simulated mean SMB for 1960–2005 is 359 ± 120 Gt yr -1 in the range of estimates from regional climate models. The simulated seasonal mass variability is comparable with mass observations from the Gravity Recovery and Climate Experiment (GRACE), with synchronous annual maximum (May) and minimum (August–September) and similar amplitudes of the seasonal cycle. CESM is able to simulate the bands of precipitation maxima along the southeast and northwest margins, but absolute precipitation rates are underestimated along the southeastern margin and overestimated in the high interior. The model correctly simulates the major ablation areas. Total refreezing represents 35% of the available liquid water (the sum of rain and melt).
54 ENVIRONMENTAL SCIENCES↗
An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events
The annual "State of the Climate" report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model and observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.
54 ENVIRONMENTAL SCIENCES↗
Convection-Permitting Ensembles of an Isolated Mountain Thunderstorm during RELAMPAGO/CACTI
Abstract The north–south-oriented Sierras de Córdoba (SDC) ridge in central Argentina is noted for initiating thunderstorms that may grow into intense mesoscale convective systems (MCSs). It also initiates more isolated, shorter-lived cells under weaker synoptic forcing. These cells are less impactful than MCSs but may be difficult to predict in convective-scale numerical weather prediction (NWP) due to their strong sensitivities to subgrid and partially resolved processes. To study the mechanisms and predictability of such cells, convection-permitting ensemble simulations were conducted of an isolated, diurnally forced SDC thunderstorm during Cloud, Aerosol, and Complex Terrain Interactions (CACTI)/Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO). The rich observational data facilitated detailed ensemble verification, where dry biases in the surface energy balance and soil moisture were identified. These biases promoted rapid removal of convective inhibition and an early onset of precipitating cells over the SDC that were shallower and weaker than the observed cell. Correction, and then overcorrection, of the soil moisture bias in two successive ensembles was required to rectify the surface energy balance and improve the representation of the SDC cell. Nevertheless, substantial ensemble variability in convective precipitation was found, with some members producing more widespread convection than observed and others producing no deep convection at all. This variability was largely explained by a combination of thermodynamic and dynamic mechanisms, dominated by a positive sensitivity of convective precipitation to preconvective moist instability over the ridge. Secondary sensitivities were found to low-level upward mass flux and midlevel cross-barrier winds, the latter of which caused gravity waves with elevated downdrafts that tended to suppress incipient clouds.
Lopez, Andres [Department of Atmospheric and Ocean↗
Data-Driven Specification of Earth's Magnetic Field
As our society is increasingly dependent on technologies in space, predicting space weather becomes ever more important. We have come to rely on technologies such as cellphones, GPS, the Internet, and other commercial and military assets. In order to protect these systems a high priority is to develop better understanding of the harmful conditions of space weather encountered in the near-Earth radiation environment which are mostly dictated by the dynamics of energetic charged particles. The main objective of our proposal was to improve the specification and forecast of the particle distribution in the Earth’s inner magnetosphere using data assimilation together with machine learning (ML) algorithms in our ring current-atmosphere interactions model with self-consistent magnetic and electric fields (RAM-SCBE). Specifically, we explored the application of machine learning algorithms to emulate and improve, through infusion of observational data, the magnetic field (SCBE) of our ring current model. Our work advanced towards the characterization of the RAM-SCBE particle flux field and its potentially different simulation scenarios. We explored how the model behaves in a number of simulation scenarios in order to better understand how the model reacts to perturbations in the solar wind. We were able to capture this behavior through the simulation of an ensemble of RAM-SCB model solutions. The ensemble showed the important correlations between the particle fluxes and the magnetic field. We were able to start the training of a neural network (Autoencoder) to identify the dominant features of the magnetic field, and the main correlations (linear and non-linear) between the particle fluxes and the magnetic field. Our next steps consists of training a neural network to capture the time evolution of the dominant features and obtain a consistent surrogate model for the RAM-SCB.
42 ENGINEERING↗
Pan-chromatic observations of the recurrent nova LMC 2009a (LMC 1971b)
Nova LMC 2009a is confirmed as a recurrent nova (RN) from positional coincidence with nova LMC 1971b. The observational data set is one of the most comprehensive for any Galactic or extragalactic RN: optical and near-IR photometry from outburst until over 6 years later; optical spectra for the first 6 months, and Swift satellite ultraviolet (UV) and X-ray observations from 9 days to almost 1 year post-outburst. We find M{sub V} = −8.4 ± 0.8{sub r} ± 0.7{sub s} and expansion velocities between 1000 and 4000 km s{sup −1}. Coronal line emission before day 9 indicates shocks in the ejecta. Strengthening of He iiλ4686 preceded the emergence of the super-soft source (SSS) in X-rays at ∼63–70 days, which was initially very variable. Periodic modulations, P = 1.2 days, most probably orbital in nature, were evident in the UV and optical from day 43. Subsequently, the SSS shows an oscillation with the same period but with a delay of 0.28P. The progenitor system has been identified; the secondary is most likely a sub-giant feeding a luminous accretion disk. Properties of the SSS infer a white dwarf (WD) mass 1.1 M{sub ⊙} ≲ M{sub WD} ≲ 1.3 M{sub ⊙}. If the accretion occurs at a constant rate, M-dot {sub acc}≃3.6{sub −2.5}{sup +4.7}×10{sup −7} M{sub ⊙} yr{sup −1} is needed, consistent with nova models for an inter-eruption interval of 38 years, low outburst amplitude, progenitor position in the color–magnitude diagram, and spectral energy distribution at quiescence. We note striking similarities between LMC 2009a and the Galactic nova KT Eri, suggesting that KT Eri is a candidate RN.
79 ASTRONOMY AND ASTROPHYSICS↗
Comet-solar wind interaction - Dynamical length scales and models
ICE magnetometer measurements at Comet Giacobini-Zinner and model simulations of comet-solar wind interactions are analyzed. The magnetometer data reveal the existence of intense hydromagnetic turbulence, a draping of the magnetic field lines to form a magnetotail, a weak shock, and a magnetic barrier region in the magnetosphere. The global models of the comet-solar wind interaction are described. The observed data and models are compared and good correlation is displayed.
Mendis, D. A.↗
A reexamination of the cosmic-ray helium spectrum and the He-3/He-4 ratio at high energies
Cosmic ray He spectral data collected by satellites in earth orbit were used to examine a recent measurement of He-3 of about 6 GeV/nucleon, an overabundance compared to predictions made with a leaky box approach. The spectral rigidity index at the time of the measurement was no more than 2.55, indicating a near-earth He-3/He-4 ratio of 0.17, although an index in the range 10-20 GV and a ratio of close to 0.24 is the usual value. New magnetic spectrometer data, however, show that a single spectral rigidity value for the near-earth He-3/He-4 ratio cannot be correct. The Fokker-Planck equation is used to demonstrate that solar modulation of the He flux yields an energy/abundance distribution close to observational data.
Webber, W. R.↗
Structure and Dynamics of the Solar Chromosphere
The problem of chromospheric dynamics and heating consists of two problems: one, concerning the magnetic network on the boundary of supergranulation cells (CB), where the oscillation period is seven minutes, and the other, concerning the cell interior (CI), where the oscillation period is three minutes. The observational data on the oscillations and the emission of radiation can be used to determine the structure and dynamics of the atmosphere provided answers are known to three critical questions, concerning: the nature of the waves powering the bright points, the origin of the observed oscillation periods and the mechanism of chromospheric heating. The recent modeling of the dynamics of the CI, which combines a sophisticated treatment of gas dynamics and radiative transfer in a one-dimensional model with empirical velocity input from the observations, answered the first of these questions: the waves powering K(sub 2upsilon), bright points are propagating acoustic waves. This firm conclusion declares invalid the model of Leibacher & Stein, which explains the observed period with standing acoustic waves in a chromospheric cavity. On the third question, the heating of the chromosphere in the CI, their model predicts that the temperature in the chromosphere is declining in the outward direction up to a height of at least I Mm most of the time, so even the time-average temperature is dropping monotonically in the outward direction, implying that lines formed in the chromosphere up to a height of at least 1 Mm appear in absorption most of the time and everywhere in the CI. The problem of the CI can be resolved with a two-component model, which combines a model for K(sub 2upsilon), bright points with a model for the background. The bright point model has the same aims as the CS94 model, except that the empirical driving from the LRK93 observations is replaced by impulsive excitation, as suggested by the properties of the Klein-Gordon equation.
Kalkofen, Wolfgang↗
Modeling the Absorbing Aerosol Index
We propose a scheme to model the absorbing aerosol index and improve the biomass carbon inventories by optimizing the difference between TOMS aerosol index (AI) and modeled AI with an inverse model. Two absorbing aerosol types are considered, including biomass carbon and mineral dust. A priori biomass carbon source was generated by Liousse et al [1996]. Mineral dust emission is parameterized according to surface wind and soil moisture using the method developed by Ginoux [2000]. In this initial study, the coupled CCM1 and GRANTOUR model was used to determine the aerosol spatial and temporal distribution. With modeled aerosol concentrations and optical properties, we calculate the radiance at the top of the atmosphere at 340 nm and 380 nm with a radiative transfer model. The contrast of radiance at these two wavelengths will be used to calculate AI. Then we compare the modeled AI with TOMS AI. This paper reports our initial modeling for AI and its comparison with TOMS Nimbus 7 AI. For our follow-on project we will model the global AI with aerosol spatial and temporal distribution recomputed from the IMPACT model and DAO GEOS-1 meteorology fields. Then we will build an inverse model, which applies a Bayesian inverse technique to optimize the agreement of between model and observational data. The inverse model will tune the biomass burning source strength to reduce the difference between modelled AI and TOMS AI. Further simulations with a posteriori biomass carbon sources from the inverse model will be carried out. Results will be compared to available observations such as surface concentration and aerosol optical depth.
Penner, Joyce↗
NASA DEVELOP’s User-Centric Approach to Building Capacity to Use Earth Observations for Decision Making
The DEVELOP Program, part of NASA’s Applied Sciences, conducts 50-60 feasibility studies annually that center on user needs. Each project is tailored to its partner’s decision making processes with the goal of identifying and implementing opportunities for Earth observation data and information to be integrated into environmental decision making processes. These projects are conducted by a team of early career professionals through a 10-week term where the DEVELOP team rapidly iterates with partners culminating in a “recipe” for using NASA Earth observations. This presentation will introduce the DEVELOP model for user-centered design of projects, share the program's iterative approach to project execution, highlight multiple case studies, and lessons learned in the program’s model evolution.
Capacity Building↗
Science Workflows using Kamodo
Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.
software↗
Science Workflows using Kamodo
Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.
python↗
Simultaneous measurement of stratospheric O3, H2O, CH4, and N2O profiles from infrared limb thermal emissions
Thermal emission measurements of the earth's stratospheric limb were made with a cryogenically cooled high-resolution Michelson interferometer on a balloon flight launched from Palestine, TX, on Nov. 6, 1984. Infrared spectra for complete limb sequences were obtained over portions of the 700-1940/cm range with an unapodized spectral resolution of 0.03/cm for tangent heights varying from 13 to 39 km. The observed data from 1125 to 1425/cm have been analyzed for simultaneous measurement of O3, H2O, CH4, and N2O profiles. The analysis employs line-by-line and layer-by-layer radiative-transfer calculations, including curvature and refraction effects. The optimum use of geometric and spectral effects is made to obtain sharply peaked weighting functions. Contributions from stratospheric aerosol are included by measuring the light extinction within the window regions of the observed spectra. The retrieved constituent profiles are compared with measurements made with a variety of techniques by other groups. The comparison shows good agreement with the published data for all gases, indicating the capability of retrieving trace gas profiles from high-resolution thermal emission limb measurements.
Abbas, M. M.↗
Solar neutron emissivity during the large flare on 1982 June 3
For the solar neutron event on June 3, 1982, it is shown here that the combined SMM Gamma Ray Spectrometer and Jungfraujoch neutron monitor data require a time-extended emission of neutrons at the sun with energies of 100 MeV to about 2 GeV. The solar neutron emissivity spectrum is shown to have a strong downward curvature or truncation between 2 and 4 GeV. A Bessel function and truncated power law give acceptable fits to the observational data, but only the power law can explain the rapid rise of the neutron monitor count rate. The integrated emissivity of neutrons above E(n) of 100 MeV is strongly constrained at 8 x 10 to the 28th neutrons/sr and is essentially independent of neutron spectral shape. At neutron energies of about 100 MeV, good agreement is found for both spectral forms with observations of neutron decay protons.
Chupp, E. L.↗
Quantifying peat carbon accumulation in Alaska using a process-based biogeochemistry model
This study uses an integrated modeling framework that couples the dynamics of hydrology, soil thermal regime, and ecosystem carbon and nitrogen to quantify the long-term peat carbon accumulation in Alaska during the Holocene. Modeled hydrology, soil thermal regime, carbon pools and fluxes, and methane emissions are evaluated using observation data at several peatland sites in Minnesota, Alaska, and Canada. The model is then applied for a 10,000 year (15 ka to 5 ka; 1 ka = 1000 cal years before present) simulation at four peatland sites. We find that model simulations match the observed carbon accumulation rates at fen sites during the Holocene (R 2 = 0.88, 0.87, 0.38, and -0.05 using comparisons in 500 year bins). The simulated (2.04 m) and observed peat depths (on average 1.98 m) were also compared well (R2 = 0.91). The early Holocene carbon accumulation rates, especially during the Holocene thermal maximum (HTM) (35.9 g C m -2 yr -1 ), are estimated up to 6 times higher than the rest of the Holocene (6.5 g C m -2 yr -1 ). Our analysis suggests that high summer temperature and the lengthened growing season resulted from the elevated insolation seasonality, along with wetter-than-before conditions might be major factors causing the rapid carbon accumulation in Alaska during the HTM. Here, our sensitivity tests indicate that, apart from climate, initial water table depth and vegetation canopy are major drivers to the estimated peat carbon accumulation. Finally, when the modeling framework is evaluated for various peatland types in the Arctic, it can quantify peatland carbon accumulation at regional scales.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Inflationary universe in the presence of a minimal measurable length
In this paper, we will study the effect of having a minimum measurable length on inflationary cosmology. We will analyze the inflationary cosmology in the Jacobson approach. In this approach, gravity is viewed as an emergent thermodynamical phenomena. We will demonstrate that the existence of a minimum measurable length will modify the Friedmann equations in the Jacobson approach. We will use this modified Friedmann equation to analyze the effect of minimum measurable length scale on inflationary cosmology. This analysis will be performed using the Hamiltonian-Jacobi approach. We compare our results to recent data, and find that our model may agree with the recent data. - Highlights: • We study the inflationary cosmology in the Jacobson thermodynamic approach. • We analyze the short distance correction to inflation from a minimum measurable length. • This analysis is done using the Hamiltonian-Jacobi approach. • This model of inflationary cosmology is consistent with the observational data.
79 ASTRONOMY AND ASTROPHYSICS↗